Wildberries Analytics MCP server

Wildberries Analytics MCP

A Wildberries seller-analytics MCP server: sales funnel, search reports, warehouse stock and CSV exports

  • 1 ★ on the repository
  • Last commit
  • MIT
MCP server

Extended access

Why this level

  • Runs a local server that reads Wildberries funnel, search and stock data with a seller token
  • Does not change prices, bids or orders
All reasons and checks
Russian stack

dias-zhanabayev/wildberries_mcp

A similar tool with a larger community: Wildberries MCP, 16 ★ on the repository

Install

Services

In your terminal, with SkillFoxx CLI

npx skillfoxx add mcp/wildberries-analytics-mcp

Detects the agents on your machine, shows the access level and pins the version.

Other ways to install

Access and checks

How we review

Extended accessThe tool runs code or makes network calls and only reads external data.

  • Runs a local server that reads Wildberries funnel, search and stock data with a seller token
  • Does not change prices, bids or orders

This is third-party code. Review the repository files before installing.

What it does

The server connects Wildberries analytics reports to Claude Desktop and Cursor. Tools are split into four groups: a sales funnel by product card over a period or by day, search reports with SERP position and top queries per product, stock by product, size and warehouse, and CSV report creation with status checks and a ZIP download available for 48 hours. All tools are read-only; the underlying Wildberries API itself is capped at three requests per minute. The server installs via uv and runs locally with uv run main.py or in Docker.

Who it is for. For Wildberries sellers and analysts who want sales and search analytics in a conversational form.

Good fit when

  • You want to compare the sales funnel across periods or products
  • You need a product's search position and the top queries driving orders
  • You need stock by warehouse and size without opening the seller dashboard

Not a fit when

  • You need to operate on prices, supplies or ad bids: the server does not offer that
  • The Wildberries API's three-requests-per-minute cap does not fit your workload

Example request

Compare this month's sales funnel with last month and show the top 20 queries for product 123456

MCP

Transport
stdio
Authentication
API key

Environment variables

WILDBERRIES_TOKEN required, secret
A seller token from the WB dashboard, API access section

Limitations

You need a Wildberries seller token with analytics access. It requires Python 3.12 and the uv package manager. The Wildberries API caps analytics requests at three per minute, so reports for many products build up slowly. The project has no PyPI release, only a source install.

How to disable. Remove the wildberries entry from your MCP client configuration and stop the process or container.

FAQ

Can the server change prices or bids?

No, every tool only reads analytics, the funnel, search data and stock.

How long until a CSV report downloads?

The report is built as a job, its status is checked with a separate tool, and the finished ZIP is downloadable for 48 hours.

Discussion

No questions or reviews yet.

Wildberries MCP

wildberries-mcp

Russian stack

MCP server for the Wildberries seller API: products, prices, stock, orders, FBS supplies, analytics, reviews and ads

MCP serverBroad access16Repository stars

Wildberries MCP search server

Wildberries MCP Server

Russian stack

A lightweight MCP server for searching Wildberries products via its public JSON API: product card, price, reviews with no browser

MCP serverExtended access2Repository stars
Russian stack

An MCP server covering all seventeen Wildberries Seller API hosts: sales, stock, product cards, prices, financial reports and reviews

MCP serverBroad access4Repository stars
Russian stack

Remote Sellmonitor MCP servers for Wildberries analytics: market and competitors, plus your own store's sales, costs and profit

MCP serverExtended access13Repository stars

README in short

The README gives a three-step quick start, Python 3.12 and uv requirements, config examples for Cursor and Claude Desktop with and without Docker, plain-language example requests, and a reference of every tool across four groups noting the three-requests-per-minute API cap.

README badge

Report a problem